Search Results - (( sequence optimization model algorithm ) OR ( using optimization strategy algorithm ))
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1
An enhanced swap sequence-based particle swarm optimization algorithm to solve TSP
Published 2021“…Since there is no known polynomial-time algorithm for solving large scale TSP, metaheuristic algorithms such as Ant Colony Optimization (ACO), Bee Colony Optimization (BCO), and Particle Swarm Optimization (PSO) have been widely used to solve TSP problems through their high quality solutions. …”
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2
Improving Attentive Sequence-to-Sequence Generative-Based Chatbot Model Using Deep Neural Network Approach
Published 2022“…An example of the DNN model is the Attentive Sequence-to-Sequence (Seq2Seq) model that was first created to tackle a problem setting in language processing. …”
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3
Development of cell formation algorithm and model for cellular manufacturing system
Published 2011“…In addition, one of the main challenges has been development of efficient algorithm for solving aforementioned model to find exact feasible optimal solution. …”
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4
Improving particle swarm optimization via adaptive switching asynchronous – synchronous update
Published 2018“…In this paper, an adaptive switching PSO (Switch-PSO) algorithm that uses a hybrid update sequence is proposed. …”
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Indexed Article -
5
Improving particle swarm optimization via adaptive switching asynchronous – synchronous update
Published 2018“…In this paper, an adaptive switching PSO (Switch-PSO) algorithm that uses a hybrid update sequence is proposed. …”
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6
Improving particle swarm optimization via adaptive switching asynchronous – synchronous update
Published 2018“…In this paper, an adaptive switching PSO (Switch-PSO) algorithm that uses a hybrid update sequence is proposed. …”
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7
A whale optimization algorithm approach for flow shop scheduling to minimize makespan
Published 2024“…The performance of the WOA is evaluated using five benchmark problems with varying numbers of jobs and machines, and the results are compared with those obtained from other algorithms reported in the literature, such as genetic algorithms and heuristic models. …”
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8
A review on particle swarm optimization algorithm and its variants to human motion tracking
Published 2014“…Particle swarm optimization (PSO) is a population-based globalized search algorithm which has been successfully applied to address human motion tracking problem and produced better results in high-dimensional search space.This paper presents a systematic literature survey on the PSO algorithm and its variants to human motion tracking. …”
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9
The development of integrated planning and scheduling framework for dynamic and reactive environment of complex manufacturing problem
Published 2008“…Next, multi-population directed genetic algorithms (MDGA) have been used to generate a number of optimal operation sequences for a real world manufacturing problem which is elaborated in Chapter 3. …”
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10
Development of intelligent evaluation system for product end-of-life selection strategy
Published 2011“…This study integrates the travelling salesman problem with genetic algorithm (TSP-GA) for finding the optimal disassembly sequence and disassembling the EOL product. …”
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11
Safe experimentation dynamics algorithm for data-driven PID controller of a class of underactuated systems
Published 2019“…Previously, SED algorithm has been applied in to control scheme of wind farm to optimize the total power production but has yet to be applied in PID tuning. …”
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12
Safe experimentation dynamics algorithm for data-driven PID controller of a class of underactuated systems
Published 2019“…Previously, SED algorithm has been applied in to control scheme of wind farm to optimize the total power production but has yet to be applied in PID tuning. …”
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13
Hybrid dynamic scheduling model for flexible manufacturing system with machine availability and new job arrivals
Published 2015“…Furthermore, due to the limitation of single rescheduling strategy to handle various disruptions, an approach that combines multiple rescheduling strategy is used to maintain efficiency and stability. …”
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14
Methods for identification of the opportunistic gut mycobiome from colorectal adenocarcinoma biopsy tissues
Published 2024“…Here, we also proposed pipelines based on a predictive model using statistical and machine learning algorithms to accurately differentiate colorectal adenocarcinoma and polyp patients from normal individuals. …”
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15
Meta-heuristic approaches for reservoir optimisation operation and investigation of climate change impact at Klang gate dam
Published 2023“…However, due to the drawbacks of the conventional algorithm as well as the heuristic algorithms handling complicated and multi-objective reservoir optimisation, the advantages of the strategy of simultaneous exploration and exploitation led to the decision to utilise meta-heuristic algorithms in this study. …”
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Final Year Project / Dissertation / Thesis -
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Fuzzy Mixed Assembly Line Sequencing and Scheduling Optimization Model Using Multiobjective Dynamic Fuzzy GA
Published 2014“…An improved genetic algorithm called fuzzy adaptive genetic algorithm (FAGA) is proposed in order to solve this optimization model. …”
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17
Efficient Entropy-Based Decoding Algorithms For Higher-Order Hidden Markov Model
Published 2019“…The required memory of this algorithm is also time independent. In addition, the optimal state sequence obtained by the EVRA algorithm is the same as that obtained by the classical Viterbi algorithm for HHMM.…”
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18
Development of Genetic Algorithm Procedure for Sequencing Problem in Mixed-Model Assembly Lines
Published 2009“…Due to NP-hard nature of sequencing problem in mixed model assembly line, a genetic algorithm is applied to cope with problem complexity and obtain a near optimal solution in a reasonable amount of time. …”
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19
Optimization of Assembly Sequence Planning Using Soft Computing Approaches: A Review
Published 2019“…This review focused on ASP modeling approach, optimization algorithms and optimization objectives. …”
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20
Energy efficient modeling and optimization for assembly sequence planning using moth flame optimization
Published 2019“…The problem was then optimized using moth flame optimization (MFO) and compared with well-established algorithms such as genetic algorithm (GA), particle swarm optimization (PSO) and ant colony optimization (ACO). …”
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